Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis

Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a pro...

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Main Author: Bateman, Scott
Other Authors: McCalla, Gordon I.
Format: Others
Language:en
Published: University of Saskatchewan 2007
Subjects:
Online Access:http://library.usask.ca/theses/available/etd-12112007-221606/
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spelling ndltd-USASK-oai-usask.ca-etd-12112007-2216062013-01-08T16:33:07Z Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis Bateman, Scott the World Wide Web the Semantic Web tag clouds e-learning information visualization folksonomy collaborative tagging metadata Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a proven organization scheme through its popularity and widespread use on the Web, little is known about its implications and how it may effectively be applied in different situations. This is due to the fact that tagging has evolved through several iterations of use on social software websites, rather than through a scientific or an engineering design process. The research presented in this thesis, through investigations in the domain of e-learning, seeks to understand more about the scientific nature of collaborative tagging through a number of human subject studies. While broad in scope, touching on issues in human computer interaction, knowledge representation, Web system architecture, e-learning, metadata, and information visualization, this thesis focuses on how collaborative tagging can supplement the growing metadata requirements of e-learning. I conclude by looking at how the findings may be used in future research, through using information based in the emergent social networks of social software, to automatically adapt to the needs of individual users. McCalla, Gordon I. Gutwin, Carl Fichter, Darlene Vassileva, Julita University of Saskatchewan 2007-12-12 text application/pdf http://library.usask.ca/theses/available/etd-12112007-221606/ http://library.usask.ca/theses/available/etd-12112007-221606/ en unrestricted I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Saskatchewan or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.
collection NDLTD
language en
format Others
sources NDLTD
topic the World Wide Web
the Semantic Web
tag clouds
e-learning
information visualization
folksonomy
collaborative tagging
metadata
spellingShingle the World Wide Web
the Semantic Web
tag clouds
e-learning
information visualization
folksonomy
collaborative tagging
metadata
Bateman, Scott
Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
description Collaborative tagging is a simple and effective method for organizing and sharing web resources using human created metadata. It has arisen out of the need for an efficient method of personal organization, as the number of digital resources in everyday lives increases. While tagging has become a proven organization scheme through its popularity and widespread use on the Web, little is known about its implications and how it may effectively be applied in different situations. This is due to the fact that tagging has evolved through several iterations of use on social software websites, rather than through a scientific or an engineering design process. The research presented in this thesis, through investigations in the domain of e-learning, seeks to understand more about the scientific nature of collaborative tagging through a number of human subject studies. While broad in scope, touching on issues in human computer interaction, knowledge representation, Web system architecture, e-learning, metadata, and information visualization, this thesis focuses on how collaborative tagging can supplement the growing metadata requirements of e-learning. I conclude by looking at how the findings may be used in future research, through using information based in the emergent social networks of social software, to automatically adapt to the needs of individual users.
author2 McCalla, Gordon I.
author_facet McCalla, Gordon I.
Bateman, Scott
author Bateman, Scott
author_sort Bateman, Scott
title Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
title_short Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
title_full Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
title_fullStr Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
title_full_unstemmed Collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
title_sort collaborative tagging : folksonomy, metadata, visualization, e-learning, thesis
publisher University of Saskatchewan
publishDate 2007
url http://library.usask.ca/theses/available/etd-12112007-221606/
work_keys_str_mv AT batemanscott collaborativetaggingfolksonomymetadatavisualizationelearningthesis
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